Forkmate

get_day

Read-only

Read the user's food diary for one day: its entries, each listed with its id and each food with its item_index, quantity and macros, and calorie/macro totals. All calorie and macro values, including carbohydrates, are estimates from USDA FoodData Central, Open Food Facts, the user's own entry or an AI assistant's estimate — approximate, not lab-measured or specific to a package or batch, and not suitable for insulin dosing (including carb counting for a meal bolus), blood-glucose prediction or any other medical decision.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`local_date`	No	YYYY-MM-DD; defaults to today.

Output Schema

TableJSON Schema

Name	Required	Description
`totals`	Yes
`entries`	Yes
`local_date`	Yes	A local date, YYYY-MM-DD.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 1, 2026

removedOutput schema / properties / entries / items / properties / created_at
```
Removed value: -{
-  "type": "string"
-}
```
addedOutput schema / properties / entries / items / properties / id / description
```
Added value: +"Identifies the entry for a later edit or deletion."
```

removedOutput schema / properties / entries / items / properties / items / items / properties / source

Removed value: -{
-  "description": "Where the macros came from (e.g. usda, off, client).",
-  "type": "string"
-}

addedOutput schema / properties / entries / items / properties / items / items / properties / unknown_macros

Added value: +{
+  "description": "Macros missing from the source data: shown as 0 but unknown, not a real zero.",
+  "items": {
+    "enum": [
+      "protein_g",
+      "carb_g",
+      "fat_g"
+    ],
+    "type": "string"
+  },
+  "type": "array"
+}

Changed1 schema field changedSep 30, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "entries": {
+      "items": {
+        "description": "One diary entry: a meal with its foods.",
+        "properties": {
+          "at": {
+            "description": "ISO-8601 UTC instant the food was eaten.",
+            "type": "string"
+          },
+          "created_at": {
+            "type": "string"
+          },
+          "id": {
+            "type": "string"
+          },
+          "items": {
+            "items": {
+              "properties": {
+                "caffeine_mg": {
+                  "type": "number"
+                },
+                "fluid_ml": {
+                  "type": "number"
+                },
+                "macros": {
+                  "description": "Calories and macros. Estimates, not lab-measured; not for insulin dosing.",
+                  "properties": {
+                    "carb_g": {
+                      "type": "number"
+                    },
+                    "fat_g": {
+                      "type": "number"
+                    },
+                    "kcal": {
+                      "type": "number"
+                    },
+                    "protein_g": {
+                      "type": "number"
+                    }
+                  },
+                  "required": [],
+                  "type": "object"
+                },
+                "name": {
+                  "type": "string"
+                },
+                "quantity": {
+                  "type": "string"
+                },
+                "source": {
+                  "description": "Where the macros came from (e.g. usda, off, client).",
+                  "type": "string"
+                }
+              },
+              "required": [
+                "name"
+              ],
+              "type": "object"
+            },
+            "type": "array"
+          },
+          "local_date": {
+            "description": "A local date, YYYY-MM-DD.",
+            "type": "string"
+          },
+          "meal": {
+            "description": "breakfast, lunch, dinner or snack, when set.",
+            "type": "string"
+          },
+          "note": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "at",
+          "local_date",
+          "items"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "local_date": {
+      "description": "A local date, YYYY-MM-DD.",
+      "type": "string"
+    },
+    "totals": {
+      "properties": {
+        "caffeine_mg": {
+          "type": "number"
+        },
+        "entry_count": {
+          "type": "integer"
+        },
+        "fluid_ml": {
+          "type": "number"
+        },
+        "local_date": {
+          "description": "A local date, YYYY-MM-DD.",
+          "type": "string"
+        },
+        "totals": {
+          "description": "Calories and macros. Estimates, not lab-measured; not for insulin dosing.",
+          "properties": {
+            "carb_g": {
+              "type": "number"
+            },
+            "fat_g": {
+              "type": "number"
+            },
+            "kcal": {
+              "type": "number"
+            },
+            "protein_g": {
+              "type": "number"
+            }
+          },
+          "required": [
+            "kcal",
+            "protein_g",
+            "carb_g",
+            "fat_g"
+          ],
+          "type": "object"
+        }
+      },
+      "required": [
+        "local_date",
+        "entry_count",
+        "totals"
+      ],
+      "type": "object"
+    }
+  },
+  "required": [
+    "local_date",
+    "entries",
+    "totals"
+  ],
+  "type": "object"
+}

First observedJul 1, 2026

TDQS

A4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), and the description adds substantial context beyond them: the exact shape of the returned data (entries with ids, item_index, quantity, macros, totals) and the critical caveat that values are estimates from varied sources and unsuitable for medical decisions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and return shape, then the disclaimer. The disclaimer is long but each clause (sources, approximation, medical exclusions) carries distinct information, so it is mostly earned rather than padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With annotations covering safety, an output schema covering return values, and 100% parameter coverage, the remaining burden is domain caveats — which the description handles thoroughly by disclosing data provenance and medical limitations. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter, and schema coverage is 100%, so the schema fully documents local_date's format and default. The description's "one day" phrasing hints at the date scope but adds no syntax or defaulting detail beyond the schema, matching the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Read the user's food diary") and scopes it precisely to "one day," which implicitly separates it from get_range and the mutation siblings. It doesn't name an alternative explicitly, so it falls just short of the top tier.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The one-day scope implies when to use it versus get_range, and the closing disclaimer clearly rules out medical uses (insulin dosing, glucose prediction). However, there is no explicit when-to-use or when-not-to-use routing to the sibling tools, leaving usage largely inferential.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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